Kayla Irish

I am a fifth-year PhD student in the Department of Statistics at the University of Washington, advised by Alex Luedtke (Departments of Health Care Policy and Statistics, Harvard University). My research focuses on the design and analysis of clinical trials, with a particular focus on covariate adjustment. I’m also interested in survival analysis and early and intermediate trial endpoints.

I’ve pursued these interests specifically in oncology trials, through a fellowship and an industry internship. As a 2025–2026 FDA Oncology Center of Excellence Fellow, I learned about regulatory policy and the practical challenges of oncology drug development. As a graduate biostatistician intern at Johnson & Johnson Innovative Medicine (Summer 2025), I used surrogate analysis of time-to-event endpoints to inform go/no-go decisions for a potential Phase III oncology trial. I’ve also worked on go/no-go decision-making more broadly: at AbbVie (Summer 2026), I used Bayesian historical control borrowing and propensity score methods for more precise go/no-go decisions across all therapeutic areas.

Before UW, I earned B.A.s in Mathematics and History from the University of Montana.

selected publications

arXiv

Simple Covariate Adjustment for Many Estimands Using Stable Balancing Weights

Kayla Irish, José Zubizarreta, and Alex Luedtke

arXiv preprint arXiv:2609.01638, 2026

arXiv Bib Code

@article{irish2026simple,
  title = {Simple Covariate Adjustment for Many Estimands Using Stable Balancing Weights},
  author = {Irish, Kayla and Zubizarreta, Jos{\'e} and Luedtke, Alex},
  journal = {arXiv preprint arXiv:2609.01638},
  year = {2026},
}